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pmid:37773841
Bioinformatics analysis of copper death gene in diabetic immune infiltration.
Zhimin Lu · Ling Ding · Sen Zhang · Xing Jiang · Qinglu Wang · Ying Luo · Xuewen Tian
Medicine · 2023 doi:10.1097/MD.0000000000035241
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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The mechanism of copper death gene regulating immune infiltration in diabetes has not been studied.\nMETHODS: Download microarray data from healthy normal and diabetic patients from the GEO database. The identification of differentially expressed genes (DEGs) was analyzed by gene enrichment. Using String online database and Cytoscape software to interact with the protein interaction network and make visual analysis. Using Wilcox analyze the correlation between the copoer death gene and diabetic mellitus. Analysis of the correlation between immune penetration cells and functions, and the difference between the diabetes group and the control group, screening the copper death gene associated with diabetes, and predicting the upper top of microRNA (miRNA) through the Funrich software.\nRESULTS: According to the identification of differential genes in 25 samples of GSE25724 and GSE95849 data sets, 328 differential genes were identified by consensus, including 190 up-regulated genes and 138 down-regulated genes (log2FC = 2, P < .01). KEGG results showed that neurodegeneration-multiple disease pathways were most significantly upregulated, followed by Huntington disease. According to Cytohubba, the TOP10 genes HCK, FPR1, MNDA, AQP9, TLR8, CXCR1, CSF3R, VNN2, TLR4, and CCR5 are down-regulated genes, which are mostly enriched in neutrophils. Immunoinfiltration-related heat maps show that Macrophage was strongly positively correlated with Activated dendritic cell, Mast cell, Neutrophil, and Regulatory T cell showed a strong positive correlation. Neutrophil was strongly positively correlated with Activated dendritic cell, Mast cell, and Regulatory T cell. Differential analysis of immune infiltration showed that Neutroph, Mast cell, Activated B cell, Macrophage and Eosinophil were significantly increased in the diabetic group. Central memory CD4 T cell (P < .001), Plasmacytoid dendritic cell, Immature dendritic cell, and Central memory CD8 T cell, etal were significantly decreased. DBT, SLC31A1, ATP7A, LIAS, ATP7B, PDHA1, DLST, PDHB, GCSH, LIPT1, DLD, FDX1, and DLAT genes were significantly associated with one or more cells and their functions in immune invasion. Forty-one miRNA.\nCONCLUSIONS: Copper death is closely related to the occurrence of diabetes. Copper death genes may play an important role in the immune infiltration of diabetes.", "claims": [{"id": "claim-method", "statement": "This study analyzed the significance of these genes in 2 groups of samples, diabetes and normal people, and made box maps by Wilcox test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37773841", "locator": "sections[10] \"2.8. Correlation analysis between copper death gene and diabetes mellitus\" paragraph 2", "quote": "This study analyzed the significance of these genes in 2 groups of samples, diabetes and normal people, and made box maps by Wilcox test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the current study are publicly available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37773841", "locator": "sections[27] \"(untitled)\" paragraph 1", "quote": "The datasets generated during and/or analyzed during the current study are publicly available."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Copper death is closely related to the occurrence of diabetes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37773841", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Copper death is closely related to the occurrence of diabetes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Copper death is closely related to the occurrence of diabetes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37773841"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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METHODS: Download microarray data from healthy normal and diabetic patien"], "order_basis": "paper_text_order:271", "id": "assay:1"}, {"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["pathway enrichment"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}